Waring: This dataset is still under preparation an not published yet!

Single layer fits of XRR measurements of softmatter thinfilms¶

This is a compiled dataset of raw XRR measurements together with corresponding fit parameters, intentionally published to use as training or test data for machine learning models.

Data structure¶

All data is provided in an hdf5 file, follwing NeXus convention with respect to the provied metadata in the hdf5 attributes. The datesets have been measured in-situ and therefore there are always stacks of curves that correspond to the diffrent layer thicknesses of the same material on top of $SiO_x$. The measured data is provied under experimental and the corresponding fit parameters under fit. Additional information is collected in metadata.

image-2.png

Layer model¶

The follwing model was used:

Air
layer 1: thicknes, roughness and SLD fitted
$SiO_x$: thicknes, roughness and SLD kept constant for each stack
$Si$: roughness and SLD kept constant

Limited q-range of fits¶

For all provied fits the q-range during fitting was limited form $q_{min} = 0.0 {\mathring{A}}^{-1}$ to $q_{max} = ?? {\mathring{A}}^{-1}$.

How to cite this data¶

Please consider citing the the folloing publication: ###

The dataset itself can be cited via the zenodo doi ###

Where to find the dataset and how to contribute¶

Have a look at github ### and zenodo ###. In case you wish to add further data to this repository, please use github pull requests and provide feedback through github issuse.

Interactive presentation of the data¶

in the following you find some plots presenting the provided experimental data & fits. Most of the dataset were measured insitu therefor there are many measured XRR curves of the same sample while the thin film was still growing (prepared via OMBD). Use the slider to browse through the stacks of curves.

In [1]:
#prepare jupyter notebook for plots shown below
%run prepare_plot.py

#imports
from silx.io.dictdump import nxtodict     #read NeXus hdf5 to python dict
import numpy as np
import pandas as pd
from IPython.display import display

#use same q_range as during fitting
q_fit = np.linspace(0.02,0.15,130,endpoint=False)

#produce plots
for key, ds in nxtodict("xrr_dataset.h5").items():
    if "@" not in key:   #skip nexus attributes
        
        print("Dataset: ",key)
        print("Experimentalists: ",ds["metadata"].pop("Experimentalists","?"))
        ds["metadata"].pop("@NX_class", "")
        display(pd.DataFrame.from_dict({"Dataset":[key],**ds["metadata"]}))
        
        fig = prepare_figure(ds,q_fit,str(ds["metadata"]["Layer_material"])+" on SiOx")
        fig.show()        
Dataset:  DIP_1
Experimentalists:  ['Kowark, Stefan']
Dataset Layer_CAS Layer_formula Layer_material Substrate_temperature Substrate_temperature@unit instrument q_max_fit q_max_fit@unit year_experiment
0 DIP_1 188-94-3 C32H16 Diindenoperylene 303 K ESRF, ID10b 0.15 1/Ang 2005
Dataset:  DIP_2
Experimentalists:  ['Hinderhofer, Alexander']
Dataset Layer_CAS Layer_formula Layer_material Substrate_temperature Substrate_temperature@unit instrument q_max_fit q_max_fit@unit year_experiment
0 DIP_2 188-94-3 C32H16 Diindenoperylene 303 K ESRF, ID10b 0.15 1/Ang 2010
Dataset:  DIP_3
Experimentalists:  ['Lorch, Christopher']
Dataset Layer_CAS Layer_formula Layer_material Substrate_temperature Substrate_temperature@unit instrument q_max_fit q_max_fit@unit year_experiment
0 DIP_3 188-94-3 C32H16 Diindenoperylene 303 K SLS, MXX04 0.15 1/Ang 2012
Dataset:  DNTT_PDIF_1to2
Experimentalists:  ['Rußegger, Nadine' 'Greco, Alessandro']
Dataset Layer_material instrument q_max_fit q_max_fit@unit year_experiment
0 DNTT_PDIF_1to2 DNTT PDIF (1:2) DESY, P08 0.15 1/Ang 2021
Dataset:  DNTT_PDIF_2to1
Experimentalists:  ['Rußegger, Nadine' 'Greco, Alessandro']
Dataset Layer_material instrument q_max_fit q_max_fit@unit year_experiment
0 DNTT_PDIF_2to1 DNTT PDIF (2:1) DESY, P08 0.15 1/Ang 2021
Dataset:  PDIC5
Experimentalists:  ?
Dataset Layer_material Substrate_temperature Substrate_temperature@unit q_max_fit q_max_fit@unit
0 PDIC5 PDIC5 303 K 0.15 1/Ang
Dataset:  PDIC8
Experimentalists:  ?
Dataset Layer_material Substrate_temperature Substrate_temperature@unit q_max_fit q_max_fit@unit
0 PDIC8 PDIC8 303 K 0.15 1/Ang
Dataset:  PDIC8CN2_DIP_1to1
Experimentalists:  ?
Dataset Layer_material Substrate_temperature Substrate_temperature@unit q_max_fit q_max_fit@unit
0 PDIC8CN2_DIP_1to1 PDIC8CN2 DIP (1:1) 303 K 0.15 1/Ang
Dataset:  PEN_1
Experimentalists:  ['Dax, Ingrid']
Dataset Layer_formula Layer_material Substrate_temperature Substrate_temperature@unit instrument q_max_fit q_max_fit@unit year_experiment
0 PEN_1 C22H14 Pentacene 300 K lab source 0.15 1/Ang 2021
Dataset:  PEN_2
Experimentalists:  ['Dax, Ingrid']
Dataset Layer_formula Layer_material Substrate_temperature instrument q_max_fit q_max_fit@unit year_experiment
0 PEN_2 C22H14 Pentacene LT lab source 0.15 1/Ang 2021
In [ ]: